Emission Mitigation Research Articles

Reduction of Green House Gases Emission: Towards a Sustainable Future

In the current time the climate change risk has continued to intensify such that sustainability of the world is difficult, hence urgent emission mitigation actions. An in-depth analysis of GHG emission reduction policies is provided in this paper, with a focus on strategies involving technology, policy, society, and the economy. Regulations play a significant role in reducing the amount of carbon in the atmosphere, which gives a framework for the development of incentives for all sectors. The social cost of carbon is internalized by carbon pricing strategies like carbon taxes and cap-and-trade programs, which promote businesses to invest in greener practices and technological advances. Based on market structures, standards for energy efficiency and mandates for emissions targets may act as catalysts for changes in the market that push towards such low-carbon options. If a significant reduction in greenhouse gas emissions from major economic sectors like agriculture, industry, transportation, or energy is to be achieved, technological advancement will continue to be crucial. Consequently, renewables including solar power wind turbine systems and hydroelectricity plus others replaced fossil fuelled-based sources thereby reducing emission in generation of electrical power. Further, this is to be achieved through efforts in grid modernization, smart infrastructural development and energy storage facilitating the penultimate connection of vast amount of renewable power to electricity grids especially during peak times. Again, industrial sector seems promising as far as decarbonizing production processes and reducing emissions are concerned by adopting clean technologies such as carbon capture and storage (CCS), electrification and sustainable manufacturing processes. Additionally, changes that result into modification in the transport sector like electric vehicles expansion of public transportation systems, promotion of active transport modes amongst others also reduces emission levels whilst enhancing air quality. Transitioning to a low-carbon economy through financing will therefore require significant mobilization of investments towards clean energy infrastructure, sustainable land use practices and climate-resilient development. To direct capital towards low-carbon investment green bonds, carbon markets and public-private partnerships provide innovative financing mechanisms.

Carbon emission disclosure in the agriculture industry in Indonesia: The determinant factors

The agriculture industry in Indonesia, despite its huge contribution to the country’s economy, is responsible for a substantial amount of carbon emissions. Hence, according to the country’s stock exchange regulation, agriculturally listed companies shall annually report their carbon emissions and carbon emission mitigation. The main objective of our research is to analyze the factors that influence the reporting of greenhouse gas emissions by agriculture corporations. The examined factors are environmental performance, which is assessed through environmental performance ratings and environmental management certification, the released sustainability report, ownership structure, and financial characteristics. Using 91 publicly traded agriculture companies from 2019 to 2022 as a sample, the ordinally least squares regression analysis shows that publications of a company’s carbon emissions tend to rise in accordance with both the rating of its environmental performance and the issuance of its sustainability report. Institutional ownership and financial characteristics of a company do not have any relationship with the extent of carbon emission disclosures. This study delivers an understanding to the Financial Service Authority Agency that the environmental performance rating assessment by the KLH and the yearly sustainability report encourage companies to do activities related to environmental sustainability.

Feasibility analysis and Atlas for green hydrogen project in MENA region: Production, cost, and environmental maps

Renewable energy markets in the Middle East and North Africa (MENA) countries are growing quickly. Therefore, the objective of the current study is to investigate the feasibility of green hydrogen production based on the meteorological conditions within each MENAcountry utilizing a water electrolysis system powered by available solar and wind energies. In addition, it shows the opportunities for constructing hydrogen projects in MENA countries based on the available power, system performance, cost, and CO2 emission mitigation. The simulation is conducted using MATLAB/Simulink software. In addition, five degradation rates are examined in economic analysis in the context of hydrogen production from photovoltaic panels and wind turbines due to the unpredictability of the future value of money. The results revealed that the highest hydrogen production density for WT/H2 is 1.29 kg/m2 in Morocco, 1.26 kg/m2 in Egypt, 5.7 kg/m2 in Saudi Arabia, and 5.58 kg/m2 in Egypt for PV/H2. The WT/H2 system is more efficient than the PV/H2 system, with a maximum value of 31.54 %. The minimal production cost is 2.12 $/kg in Morocco and 2.17 $/kg in Egypt for the WT/H2. In the case of PV/H2, it is 3.28 $/kg in Saudi Arabia and 3.35 $/kg in Egypt. MENA countries have significant potential in hydrogen production and hydrogen investment. The range of CO2 mitigation lies between 11.47 and 87.4 kgCO2/m2. Finally, the current investigation revealed that the MENA region has an excellent opportunity to construct green hydrogen production projects based on wind/solar energies.

Appraising Kenyan energy demand policies for energy efficiency improvement and GHG emissions mitigation

Like in most Sub-Saharan Africa, biomass is the most consumed fuel in overall Kenyan energy demand. In addition to biomass, other end-use fuels are also consumed in the country, mostly by economic sectors. However, electricity demand has been the only end-use energy considered in most energy planning studies conducted for the country. There is a need to develop robust energy planning policies considering all end-use fuels demand in order to give insights on overall supply needed by residential and economic sectors of the country. Therefore, this study used LEAP “Low Emissions Analysis Platform” model to analyze the country's total energy demand in all sectors. Results show that the country's total energy demand would keep rising; this was 685.4 PJ in 2015 and would grow up to 857.5 PJ in 2040. The residential sector would remain the main consumer of total final energy as its consumption would constitute 79.6 % of total energy demand by 2040. Firewood and charcoal would remain the main consumed fuels, especially for cooking while electricity would stay the main consumed energy for lighting. Three energy policies (universal electrification -UE, efficient lighting - EL and efficient cooking stoves -EFCS), found strategic priorities by the Kenyan Government, were analyzed. While the UE will require the country to increase its power supply, the implementation of EL and EFCS policies for highly consumed fuels would enable to save a significant amount of energy, reduce a high rate of deforestation and mitigate GHG emissions. This study would help Kenyan policymakers to strategize on all-fuels energy supply in order to meet the total energy demand.

Assessment of Carbon-Dioxide Emission from Non-Road Equipment Construction Sources at a Flyover Development Site in Port Harcourt, Nigeria

It is emphasized that global warming and climate change vary directly with the increase in the concentration of greenhouse gases, particularly carbon dioxide across domains. The constructions of social and economic infrastructures in developing counties such as Nigeria at a higher rate increases the emissions of carbon dioxide (CO2) into the lower atmosphere. Non-road construction equipment sources powered by fossil fuels are considered to be primary emitters of greenhouse gases during the construction stages of large infrastructure project. In this study, inventory of non-road construction machinery emissions from the Tank junction flyover construction site along East-West Road in Port Harcourt metropolis were estimated via field data gathering. Results showed that an average of about 398.7 g/s (4134.4 ton/year) of CO2 is released from the construction site in Port Harcourt, Nigeria. Among the various types of non-road engines considered, the mobile crane was the largest single contributor to the total CO2 emissions, accounting for 18.5%. Machinery with power above 300 kW were 8 out of 30 equipment on site and accounted for the largest share (52.87%) of total CO2 emissions. Based on the findings from current research literature and the case study, control strategies such as enforcing standards and policy, conducting impact assessment, adopting low carbon technology, and restricting energy utilization need to be implemented in other reduce the impact of global warming and alleviate climate change. Therefore, CO2 emission mitigation plans and schemes are necessary alongside standardized frameworks and guidelines. All stakeholders must play their roles efficiently to reduce CO2 emissions and aid in mitigating the effects of climate change.

Molecular composition of fresh and aged aerosols from residential wood combustion and gasoline car with modern emission mitigation technology.

Emissions from road traffic and residential heating contribute to urban air pollution. Advances in emission reduction technologies may alter the composition of emissions and affect their fate during atmospheric processing. Here, emissions of a gasoline car and a wood stove, both equipped with modern emission mitigation technology, were photochemically aged in an oxidation flow reactor to the equivalent of one to five days of photochemical aging. Fresh and aged exhausts were analyzed by ultrahigh resolution mass spectrometry. The gasoline car equipped with a three-way catalyst and a gasoline particle filter emitted minor primary fine particulate matter (PM2.5), but aging led to formation of particulate low-volatile, oxygenated and highly nitrogen-containing compounds, formed from volatile organic compounds (VOCs) and gases incl. NOx, SO2, and NH3. Reduction of the particle concentration was also observed for the application of an electrostatic precipitator with residential wood combustion but with no significant effect on the chemical composition of PM2.5. Comparing the effect of short and medium photochemical exposures on PM2.5 of both emission sources indicates a similar trend for formation of new organic compounds with increased carbon oxidation state and nitrogen content. The overall bulk compositions of the studied emission exhausts became more similar by aging, with many newly formed elemental compositions being shared. However, the presence of particulate matter in wood combustion results in differences in the molecular properties of secondary particles, as some compounds were preserved during aging.

Research on the Integrated Development of Nuclear Energy and Aviation Industry under the Background of 'Dual Carbon' Goals

The aviation sector, which is predominantly reliant on fossil fuels, confronts a monumental challenge in striving for net-zero CO2 emissions by the year 2050. Within the spectrum of decarbonization initiatives for the aviation industry, Sustainable Aviation Fuels (SAF) are recognized as the most viable carbon emission mitigation strategy. This study systematically reviews the technological trajectories of SAF and posits that Electrofuels, derived from the power-to-liquid (PtL) conversion process, will serve as a pivotal nexus for the synergistic development of nuclear energy and aviation. This integration is poised to facilitate the decarbonization of the conventional aviation sector. This paper introduces a conceptual framework for Nuclear-Derived Sustainable Aviation Fuel (ND-SAF).

Low-carbon supply chain coordination through dual contracts considering pareto-efficiency

ABSTRACT Considering the growing green awareness and increasingly stringent emission regulations, heavy-emitting supply chains are required to re-schedule their operations for environmental responsibility. Although coordination helps the supply chains overcome the decentralised disadvantages to achieve desirable profits, literature considering option contracts under emission constraints, especially combining warehousing contracts, remains scarce. This paper fills this research gap with the novelty in the dual-contract-coordinated decision analysis for achieving profit maximum and emission reduction targets considering customers’ green awareness through option and warehousing contracts, based on the originality of using the Lagrange-Stackelberg optimisation method, which overcomes the difficulty in expressing the first-mover’s decisions and simplifies the problem-solving process. Analytical and numerical results show that Pareto-efficient coordination can be fully achieved by the option contract if the warehousing contract ensures the same inventory costs before and after coordination. Otherwise, partial coordination also raises insiders’ profitability only through the option contract. Purchasing extra emissions with green investment is the best in most cases. The contract-maker should deliberate its contract settings including the option and wholesale prices, as well as warehousing, to develop Pareto-efficient coordination. Sustainability comes at a cost, but coordination raises profitability and emission mitigation in a well-built ETS market.

Towards smart sustainable cities: Does technological innovation mitigate G7 CO2 emissions? Fresh evidence from CS-ARDL

Sustainable cities are considered paradigmatic to achieve COP27 targets, but scant literature has analyzed the association with CO2 emission (CE) mitigation policies, especially for the G7 economies. This study traces the impacts of urbanization, innovation, income, and energy consumption on CE for the G7 countries from 1995 to 2019. The time period is important due to the rapid increase in urbanization, globalization, and, at the same time, technology diffusion. The study is focused on novel and relevant panel data econometric methods that tackle cross-section dependence, non-normality of data, and heterogeneity in slope coefficients. The empirical outcome first confirms the long-run cointegrating relationship among the variables in the presence of structural breaks by employing the advanced panel cointegration test. Technologies related to environmental management and energy consumption are positively linked with CE. However, the role of income per capita is found to be inverse with CE. In contrast, the effect of urbanization in different models is mixed for CE. Innovation and its interaction with urbanization are crucial for limiting CE and promoting sustainable cities in G7 economies. This indicates that urbanization with environment-friendly innovation can help G7 countries foster sustainable cities and achieve COP27 targets in general, specifically the Sustainable Development Goal of sustainable cities. The results were tested for the multiplicative effect of different variables with urbanization and innovation. Regarding policy insights, the study recommends focusing on smart and sustainable cities with environment-related innovations and transitioning towards cleaner energy from conventional energy consumption.

Feasibility of carbon-capturing in building heating systems: A life cycle thinking-based approach

Buildings are responsible for 40 % of the global energy consumption, thus leading to significant climate change and other environmental impacts. Adopting carbon capturing, storage, and utilization technologies (CCSU) can be a solution for reducing greenhouse gas (GHG) emissions from natural gas building heating systems. However, the current knowledge base lacks definitive knowledge on the possibilities and impacts of building level CCSU. The goal of this study is to investigate the feasibility of implementing CCSU technologies in natural gas building heating systems. A comparative performance assessment framework was developed to evaluate the environmental and economic performance of building-level CCSU technologies over their life cycle. These performances were then compared against alternative GHG emissions mitigation methods used for building heating systems. The results obtained by a case study indicated that adopting CCSU technologies in residential buildings is not economically and environmentally competitive against electricity-based heating systems when the regional electricity is generated using renewable energy sources and nuclear energy. However, there is a potential for the building-level CCSU in regions that depend on fossil fuels to generate electricity. The research outcomes will further develop and improve building-level carbon capturing technologies and will provide confidence to stakeholders to invest.

Natural resources-financial innovation-carbon neutrality nexus: The role of policy robustness

This study sought to investigate the impact of a natural resources, financial innovation, and policy robustness on carbon neutrality of a nation. Cross-country data from 6 major Asian economies: China, Malaysia, India, Indonesia, Pakistan, and Japan, from 2010 to 2020, were drawn for the analysis. This study employed the Westerlund panel cointegration approach to examine the long term relationship among the variables. Three models were developed and analyzed keeping CO2 emissions, natural resources, and financial innovation as dependent variables. Our findings of model-1 revealed that abundant natural resources and increase financial innovation are linked to lower carbon emissions. Policy robustness plays a significant role in reducing carbon emissions, highlighting the importance of strong environmental policies for sustainable development. However, economic growth is associated with higher carbon emissions, suggesting the need to manage growth sustainably. As economies expand, the consumption of natural resources also increases, indicating the necessity for strategies to decouple economic growth from resource use. In the model-2, GDP positively influences the exploitation of natural resources, emphasizing the need for sustainable practices. In the model-3, financial innovation is positively related to carbon emissions, indicating the potential for innovative financial instruments in emissions mitigation. Conversely, a negative relationship between natural resources and financial innovation suggest the importance of sustainable financial practices. This study stresses the complexity of factors influencing environmental sustainability and calls for comprehensive research. It underscores the significance of combining economic development with sustainable resource use, innovative financial practices, and robust policy frameworks to foster environmental sustainability in the Asian context.

Integrating work into life helps reduce residential greenhouse gas emissions

Work from home (WFH) creates work–life integration by moving work into traditional life at home, but its influence on residential greenhouse gas (GHG) emissions remains unclear. In this study, an activity-based bottom-up model was developed to analyze the time-use patterns (activity durations and timeline of a typical day) of participants under WFH and traditional home life and to quantify their residential GHG emissions. Under WFH, participants generated an average of 9.03 kg CO2e/person/day, primarily attributed to space heating and cooling, cooking, grooming, work, and watching TV and movies. Notably, the GHG footprints varied across groups (8.08–9.93 kg CO2e/person/day) due to different work and household responsibilities and leisure time and varied with climate region (4.99–10.63 kg CO2e/person/day) because of emission factors of electricity, space heating and cooling, and cooking. Compared with traditional life at home (10.06 kg CO2e/person/day), WFH participants spent less time on almost all major activities (especially sleeping and watching TV and movies) to focus on work, enabling an 11.34% (1.02 kg CO2e/person/day) mitigation of GHG emissions. The reductions also varied by group and climate region, mainly associated with laundry, cooking, and watching TV and movies. Opportunities to reduce GHG emissions under WFH lie in targeting key activities, balancing the time spent on various activities, and developing group- and spatial-specific strategies. This study provides a systematic and high-resolution estimation of residential GHG emissions under WFH and traditional home life, with a complete system boundary, activity-specific considerations, and countrywide understanding. The findings reveal the environmental impact of work–life integration from the residential perspective and can aid residents and policymakers in utilizing decarbonization opportunities to advance low-carbon living under WFH.

Forecasting the energy demand and CO2 emissions of industrial sectors in China's Beijing-Tianjin-Hebei region under energy transition.

As the world's greatest energy consumer, China's energy consumption and transition have become a focus of attention. The most significant location for regional integration in the north of China is the Beijing-Tianjin-Hebei region, where the industrial sector dominates its energy consumption. Forecasting the energy demand and structure of industrial sectors in China's Beijing-Tianjin-Hebei region may help to promote the energy transition and CO2 emission mitigation. This study conducts a model based on the year 2020 using the Long-Range Energy Alternatives Planning System (LEAP) software and sets two scenarios (baseline scenario and emission peak scenario) to forecast the future energy demand and CO2 emissions of industrial sectors in China's Beijing-Tianjin-Hebei region until the year 2035. Moreover, the industrial sectors are classified into traditional high-energy-consuming industries, emerging manufacturing industries, daily-related light industries, and other industries. The forecasting results show that (1) The industrial energy demand of the entire Beijing-Tianjin-Hebei region will grow from 234 Mtce in 2020 to 317 Mtce in 2035, and the corresponding energy structure will shift from coal-based to electricity-based; (2) at the provincial level, all three provinces will experience an increase in industrial energy demand between 2020 and 2035, with Hebei experiencing the fastest average annual growth rate of 2.18% and the largest share of over 80%, and Beijing experiencing the highest average annual electrification rate of 70%; (3) at the industrial sector level, the electricity and natural gas will gradually replace other energy sources as the main energy source for industry. The most representative industrial sub-sector in Beijing, Tianjin, and Hebei provinces are all traditional high-energy-consuming industries, which will account for more than 90% of the total energy demand in both Tianjin and Hebei by 2035.

Perovskite Solar Cell: Chemical Composition and Bandgap Energy via Machine Learning

The exponential growth in publications and applications of perovskite photovoltaic cells highlights their significance in energy conversion and carbon emissions mitigation. From 2009 to 2023, the efficiency of these cells has significantly increased from 3.9% to 25.7%. The adaptive capacity of perovskite structures for solar spectrum absorption and current displacement is strongly influenced by the bandgap energy, ideally situated between 1.3 and 1.7 eV. Although various perovskite compositions can potentially attain this energy range, the synthesis methodologies remain empirically driven, presenting challenges to experimental viability. In this context, leveraging experimental databases provided by global researchers emerges as an effective approach to expedite and enable research on perovskite structures for photovoltaic cells. This study utilized the comprehensive MaterialsZone database to feed machine learning algorithms, focusing on Support Vector Machine (SVM) and Random Forest (RF) methodologies to predict the bandgap energy in a targeted perovskite composition. By conducting synthesis experiments towards specific compositions guided by model predictions, it becomes feasible to efficiently achieve the desired bandgap energy. Such a strategy not only accelerates research progress but also serves to curtail costs associated with the synthesis of perovskite materials. The RF model exhibited an average percentage error of 5.13%, a standard deviation of the percentage error of 6.99%, and a Root Mean Square Error (RMSE) of 0.119. In contrast, the SVM model recorded an average percentage error of 4.05%, a standard deviation of the percentage error of 6.45%, and RMSE of 0.881. These developed models not only demonstrate high predictive capacity but also contribute substantively to the comprehension of the intricate relationship between the chemical composition and bandgap energy values of perovskites. By deploying machine learning algorithms, this work paves the way for targeted optimizations and considerable strides in the manufacturing of perovskite-based photovoltaic cells.

Evaluation of Bottom-UP Methodologies in Estimating Atmospheric Emissions from Ships: A Case Study of the Itaguaí-RJ Port Complex

Objective: The present study aims to evaluate the two main bottom-up emission estimation methodologies adopted worldwide for preparing vessel emissions inventories, in order to verify their limitations, as well as best practices. Theoretical framework: This study was conducted based on a bibliographical survey of methodologies adopted to estimate emissions, with the premise being the impact on the environment as a result of maritime transport. Methodology: The two most adopted methodologies, AP-42 from the United States Environmental Protection Agency (USEPA, 2009) and the European Environment Agency (EEA, 2019), were selected to estimate pollutant and Greenhouse Gas (GHG) emissions from vessels during hoteling in the Itagui Port Complex (IPC), from 2017 to 2021. Additionally, the study evaluates the application of methodologies in constructing an emissions inventory. Results and conclusion: The results indicate that container ships were identified as the largest sources of pollution by the EEA methodology (2019), unlike the USEPA method (2009), which identifies bulk carriers. Adopting the EEA (2019) methodology, total emissions were higher than USEPA (2009), up to 45 times higher for NOx and 174 times for PM10, while for SO2 it differs by only 26%. Implications of the research: The study is of fundamental relevance, as choosing the most appropriate methodology for estimating emissions is a crucial step for air quality management and emission mitigation measures. Originality/value: This research has social, scientific and environmental value carried out with real data, implying originality in the discussions presented.

In situ simultaneous measuring method for the determination of key processes of soil organic carbon cycling: Soil microbial respiration using laser spectrometry.

Soil microbial heterotrophic C-CO2 respiration is important for C cycling. Soil CO2 differentiation and quantification are vital for understanding soil C cycling and CO2 emission mitigation. Presently, soil microbial respiration (SR) quantification models are based on native soil organic matter (SOM) and require consistent monitoring of δ13C and CO2. We present a new apparatus for achieving in situ soil static chamber incubation and simultaneous CO2 and δ13C monitoring by cavity ring-down spectroscopy (CRDS) coupled with a soil culture and gas introduction module (SCGIM) with multi-channel. After a meticulous five-point inter-calibration, the repeatability of CO2 and δ13C values by using CRDS-SCGIM were determined, and compared with those obtained using gas chromatography (GC) and isotope ratio mass spectrometry (IRMS), respectively. We examined the method regarding quantifying SR with various concentrations and enrichment of glucose and then applied it to investigate the responses of SR to the addition of different exogenous organic materials (glucose and rice residues) into paddy soils during a 21-day incubation. The CRDS-SCGIM CO2 and δ13C measurements were conducted with high precision (<1.0µmol/mol and 1‰, respectively). The optimal sampling interval and the amount added were not exceeded 4 h and 200mg C/100g dry soil in a 1 L incubation bottle, respectively; the 13C-enrichment of 3%-7% was appropriate. The total SR rates observed were 0.6-4.2µL/h/g and the exogenous organic materials induced -49%-28% of priming effects in native SOM mineralisation. Our results show that CRDS-SCGIM is a method suitable for the quantification of soil microbial CO2 respiration, requiring less extensive lab resources than GC/IRMS.

Oxidation dynamics of soot or carbon black accounting for its core-shell structure and pore network

Internal oxidation is most important for removal of soot in diesel particulate filters. Furthermore, it enhances the porosity of carbon blacks (CBs), increases their specific surface area, SSA, determining their performance in batteries, inks and tires, as well as their environmental and health impact. Current models for oxidation of soot or CB neglect its fractal-like pore network during internal oxidation and underestimate its SSA by 60 % on average! Here, a lattice Monte Carlo (LMC) model elucidates both external and internal oxidation dynamics of soot (or CB) accounting for its fractal-like pore structure, for the first time to the best of our knowledge. Random internal oxidation takes place at the bulk soot (or CB), expanding its pore network and increasing the pore fractal dimension, Dfp, up to 3, in good agreement with data. This increases the SSA up to a factor of ten at 75 % conversion. In the presence of a less reactive shell though, internal oxidation stops after the reactive core is consumed. Thus the SSA levels off at large conversions (>50 %). Hence, accounting for the realistic core-shell, fractal-like pore structure during simultaneous external and internal oxidation nicely explains several measurements of soot and CB Dfp, SSA and particle diameter. So the LMC-derived oxidation dynamics of soot or CB presented here can be used to assist the design of highly porous CB grades from first principles, as well as the mitigation of soot emissions by enhancing their oxidation.

Estimation of greenhouse gas emissions using linear and logarithmic models: A scenario-based approach for Turkiye's 2030 vision

Turkiye pledged to considerably reduce its greenhouse gas (GHG) emissions by the year 2030 as a part of its commitment under the Paris Agreement. The problem with analyzing mitigation of greenhouse gas emissions requires generation of accurate, reliable and consistent emission forecasts. This study aimed to accurately forecast Turkiye's total CO2 emissions per capita and per capita CO2 emissions from energy industries, industrial processes and agricultural sectors till 2030 using linear and logarithmic models based on increasing and decreasing scenarios. Turkiye's total CO2 emissions per capita in 2030 could reach to 7.6 and 7.7 tons of CO2, with total emissions of about 635 and 643 million tons (Mt) based on linear and logarithmic models, respectively. Linear modeling results showed that per capita CO2 emissions from Turkiye's energy industries, industrial processes and agricultural sectors could reach to 5.3, 0.9 and 0.9 tons in 2030, respectively, while logarithmic modeling results yielded that per capita CO2 emissions from Turkiye's energy industries, industrial processes and agricultural sectors could be 5.5, 1.1 and 0.9 tons in 2030, respectively. The accuracy of fit for linear and logarithmic models was assessed by calculating root mean square error (RMSE < 0.2036) and mean absolute percentage error (MAPE < 12.3347) values which showed that the models fitted well with the timeline data. In conclusion, Turkiye's greenhouse gas emissions can be reduced if utilization of renewable energy sources in the country's energy portfolio is increased, and the shares of energy intensive processes in the industrial and agricultural sectors are reduced.

The impact of remote working on Türkiye’s energy consumption and greenhouse gas emissions: Learning from the experiences of Covid-19 era

Remote working emerged as an important alternative to office working. Türkiye put in force this practice in certain months of 2020 and 2021 during the Covid-19 pandemic that led to serious decline in energy consumption in this period. The aim of this study is to find out the contribution of remote working on reducing fuel consumption in passenger car and electricity demand in case the country’s whole potential is used. This article also analyzes the effect of remote working practices on reducing greenhouse gas emissions. Results show that the country can reduce 1.8 million tons of oil equivalent of its’ energy consumption which corresponds to 1.66% of the total energy consumption and USD 1.4 billion with 2019 prices. With a total of 7.73 million tons CO2 eq. emissions mitigation, Türkiye will be able to reduce its transport and electricity related emissions by 3.2% and 3.79%, respectively. Therefore, considering that Türkiye is a net fossil fuel importer country and a party to the Paris Agreement, it is necessary to promote remote working as a complementary energy efficiency and climate change policy. It is beneficial to consider the effect of remote working on energy consumption, including natural gas, during energy crises.

Emerging trends of carbon emissions and foreign direct investment: accounting for ecological footprints, renewable energy, globalization, and technological innovations in BRICS

This paper investigates the intricate interplay between carbon emissions and foreign direct investment within the context of Brazil, Russia, India, China, and South Africa (BRICS) for the period spanning 2000 to 2022. In our comprehensive analysis, we incorporate ecological footprint, renewable energy, globalization, and technological innovations as exogenous variables. Employing a system of simultaneous equations across the BRICS panel, we aim to fully elucidate the proposed relationships. Our empirical findings underscore the following key insights: foreign direct investment, technological innovations, and the adoption of renewable energy sources significantly contribute to the mitigation of carbon emissions in these selected nations. However, it is essential to note that ecological footprints exhibit a positive association with carbon emissions, raising concerns on two fronts: escalating environmental degradation and increased land pressure, both of which contribute to rising ecological footprints in BRICS countries. Additionally, our analysis reveals that foreign direct investment is influenced by its capacity to reduce carbon emissions and bolster renewable energy adoption, while globalization amplifies investment trends within the BRICS nations. To address the environmental repercussions of mining activities, it is imperative to implement stringent control and regulation measures, given their potential adverse impacts, including soil pollution, acid mine drainage, erosion, biodiversity loss, excessive water resource consumption, and wastewater disposal challenges. Nevertheless, proactive steps such as recycling mining waste, adopting environmentally friendly mining equipment, combatting illegal mining, and enhancing overall mining sustainability offer promising avenues to mitigate the environmental footprint of mining operations.